Multi-model Short-Range Ensemble Forecasting at Spanish Met Institute

1. Multi-model Short-Range Ensemble Forecasting at Spanish Met Institute J. A. García-Moya, A. Callado, P. Escriba, C. Santos, D. Santos, J. Simarro NWP – Spanish Met Service AEMET 10th COSMO General Meeting Cracovia – September 2008

2. SREPS at AEMET • Multi-model Multi-boundaries. • 72 hours forecast two times a day. • Characteristics: • 5 limited area models. • 4 boundary and initial conditions • Resolution: 0.25º, 40 levels. • 20 member ensemble every 12 hours. • Time-lagged Super-Ensemble of 40 members every 12 hours. 10 th COSMO Meeting

3. Multi-model • Hirlam (http://hirlam.org). • HRM from DWD (German Weather Service). • MM5 (http://box.mmm.ucar.edu/mm5/). • UM from UKMO (UK Weather Service). • COSMO from COSMO consortium 10 th COSMO Meeting

4. Multi-Boundaries Different global deterministic models: • ECMWF • UM from UKMO (UK Weather Service) • GFS from NCEP • GME from DWD (German Weather Service) • CMC from Canadian Weather Service 10 th COSMO Meeting

5. COSMO area is the same as HRM area 10 th COSMO Meeting

6. Tasks • Implementation of LAM models • HIRLAM, HRM, MM5, UM, COSMO • each with 5 global models • Pre-process • get global data and prepare for each LAM • Post-process • probabilistic products, BMA • intranet web server • Verification 10 th COSMO Meeting

7. Tasks • COSMO implementation • Crayx1 machine • 5 global models • Vertical interpolation tool • interfacing LAM and global models • example: GFS isobaric to hybrid levels • int2lm tool can be used 10 th COSMO Meeting

8. Meteorological Framework • Main Weather Forecast issues are related with Short-Range forecast of extreme events. • Convective precipitation is the most dangerous weather event in Spain. • Several cases of more than 200 mm/few hours occurs every year. • Verification exercises are focused in precipitation using dense gauge network 10 th COSMO Meeting

9. 520 mm/24 h 10 th COSMO Meeting

10. Monitoring in real time • Intranet web server • Deterministic outputs • Maps for each member • Probability maps • 6h accumulated precipitation • 10 m wind speed • 24 h 2 m temperature trend • Ensemble mean and spread maps • EPSgrams 10 th COSMO Meeting

11. Monitoring 10 th COSMO Meeting

12. Whole Area Zoom over Spain Deterministic product 10 th COSMO Meeting

13. Probabilistic product How will be tomorrow compared with today? 10 th COSMO Meeting

14. Ensemble mean and spread Spread at key mesoscale areas 10 th COSMO Meeting

15. Z500 Bias & RMSE Bias&RMSE Z500 Implementation error for this member Despite the error the Ensemble Mean has very good verification! Good performance of COSMO members 10 th COSMO Meeting

16. Z500 10mWind >=10m/s H+24 H+24 10mWind H+24 10mWind >=10m/s H+24 >=10m/s Z500 Probabilistic Verification 10 th COSMO Meeting

17. Verification exercise • 24h accumulated precipitation • forecast 06UTC-06UTC against observed 07UTC-07UTC • Checked in HH+030 and HH+054 • 90 days (Apr1 to Jun30 2006). • Different rain gauge networks as references: • AEMET precipitation network (pnw) • MeteoFrance, DWD, UKMO • Joint pnw (many countries) • Verification method • Interpolation to observation points • Verification software • ECMWF Metview + Local developments • Performance scores • ECMWF recommendations 10 th COSMO Meeting

18. Joint 10 th COSMO Meeting

19. >=1mm >=5mm >=10mm >=20mm >=1mm >=5mm >=10mm >=20mm Reliability & Sharpness • Good reliability according to • thresholds (base rate) • forecast length H+30 Joint H+54 10 th COSMO Meeting

20. 0.5 0 1 1 Resolution • Good resolution • ROC Areas • BSSs • Good RV curves 10 th COSMO Meeting

21. Conclusions • A Multi-model-Multi-boundaries Short Range Ensemble Prediction System (MMSREPS) has been develop at the INM-Spain. • We show here a 3 months verification, 24 hour of accumulated precipitation, dense net of gauge observations. • Verification shows quite good results 10 th COSMO Meeting

22. References • (2001) Hou D., Kalnay E., & Droegemeier, K.K.: Objective Verification of the SAMEX’98 Ensemble Forecasts. M.W.R., 129, 73-91. • (1999) Buizza R., Miller, M., & Palmer, T.N.: Stochastic representation of model uncertainties in the ECMWF Ensemble Prediction System. Q. J. R. Meteorol. Soc., 125, 2887-2908. • (1997) Toth Z., & Kalnay E.: Ensemble Forecasting at NCEP and the breeding method. M.W.R., 125, 3297-3319. • (1997) Palmer T.N., Barkmeier J., Buizza R., & Petroliagis T.: The ECMWF Ensmble Prediction System. Meteorol. Appl., 4, 301-304. • (2004) Palmer, T.N., et al.: Development of a European multi-model ensemble system for seasonal to inter-annual prediction (DEMETER). B.A.M.S., 85, 853-872. • (2005) Arribas A., Robertson K.B., & Mylne, K.R.: Test of Poor Man’s Ensemble Prediction System. M.W.R., 133, 1825-1839 10 th COSMO Meeting

23. Acknowledgements • Eugenia Kalnay (Univ. Of Maryland) • Ken Mylne, Jorge Bornemann (MetOffice) • Detlev Majewski, Michael Gertz (DWD) • Metview Team, Martin Leutbecher (ECMWF) • Chiara Marsigli, Ulrich Schättler (COSMO) • Olivier Talagrand (LMD) • We also like to thank many Met. Services for making their climate network precipitation observations available to us for verification (some of them not yet included): Arpa-Sim-Bolonia (Italy), DWD (Germany), EARS (Slovenia), HNMS (Greece), HMS (Hungary), KNMI (Netherlands), Lombardia (Italy), Météo-France (France), NIMH (Bulgaria), NMAP (Romania), SHMU (Slovakia), UKMO (UK), ZAMG (Austria), Cerdeña (Italy), Marche (Italy), Trento (Italy), Venezia (Italy), FMI (Finland), IMP (Portugal) 10 th COSMO Meeting

24. Thank you for your attention 10 th COSMO Meeting